TSBT71: Engineering Bytes
"I think books are like people, in the sense they turn up in your life when you most need them. -Emma Thompson"
My dearest reader, August is in full swing, and with it come more festivals, like the Fringe Festival in Edinburgh.
I recently wrote about speaking at the United Nations Open Source Week 2026 held in New York. Have a read and let me know your thoughts on the whole open source and AI deal.
What It Actually Takes to Stay Relevant as a Software Engineer in the Age of AI: We should embrace AI as a tool for productivity, learning new skills while we focus on delivering real value and making judgement calls.
Announcing Open Knowledge Compiler: a compiler for the Open Knowledge Format. Open Knowledge Compiler (OKC) is an open-source tool that converts existing documentation into the Open Knowledge Format (OKF), a vendor-neutral standard for representing knowledge as interconnected Markdown files with YAML front matter. The goal is to make organisational knowledge portable, version-controlled, and interoperable across different AI tools, enabling developers to maintain a single source of truth that both humans and AI systems can consume without relying on proprietary platforms or custom integrations.
Why I don’t recommend Tailwind CSS: Tailwind CSS is good for prototyping, but for long-term projects it makes HTML components harder to read and discourages developers from learning CSS fundamentals. Rather than treating it as the default choice, we should encourage developers to invest in native CSS skills.
AI-Assisted Engineering: Measure Outcomes, Not Activity: Teams should measure whether AI actually improves software delivery by reducing review effort, increasing successful task completion, improving code quality, reducing rework, and delivering business value. AI should be treated as a platform capability, similar to cloud infrastructure, where success is measured by trusted, consistent, and cost-effective outcomes rather than simply more AI-generated activity.
The death and revival of the hands-on Engineering Manager: In the past, engineering managers often drifted away from coding as meetings and people management consumed their time, making it harder to stay technically credible. With the rise of AI, managers can now focus on automating repetitive workflows, fixing long-standing issues, improving internal tooling, and building solutions that make their teams more productive.
The Senior Engineer’s Trap: When Your Own Expertise Becomes the Bottleneck: Senior engineers create leverage by mentoring others, sharing knowledge, improving systems and processes, making architectural decisions, and solving organisational problems that enable the entire team to perform better. The career growth of a senior engineer comes from shifting from being the person who solves every technical problem to the person who helps the team solve problems more effectively, measuring success by collective outcomes rather than individual contributions.
Stop Being an AI Babysitter: How to Use LLMs Without Losing Code Ownership: Developers should now become directors who guide LLMs with architectural intent from the start. We should define contracts, acceptance criteria, and system boundaries first, then use AI to implement small, well-scoped pieces.
AI agents can’t yet do open-ended AI research: While agents perform well on bounded, well-defined problems such as coding, debugging, or executing predefined workflows, they struggle with activities like scientific research, product strategy, and novel problem solving, where success depends on creativity, adapting to unexpected findings, and deciding what to investigate next.
The Disappearing Senior: AI and Entry-Level Jobs: As AI automates much of entry-level work, companies are unintentionally removing the apprenticeship that develops future technical leaders. Today’s senior engineers remain valuable because of their judgment and experience. However, there is a growing concern that organisations are optimising for short-term productivity at the expense of long-term talent development.
The word of the day is lol. To loll is to hang loosely, droop, or dangle.
Example in a sentence:
After playing fetch in the heat, the exhausted dog sat under a shade tree with its tongue lolling out of its mouth.
I am making my grand departure into the unknown.
Take care of yourself!
Until the next fortnight, my treasured reader, go forth, and may the odds be ever in your favour! 👏 🤖 ✊ ☠️ 🏹 🪖
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